Dimensionality Reduction for k-Means Clustering and Low Rank Approximation

24 October 2014

Papers citing "Dimensionality Reduction for k-Means Clustering and Low Rank Approximation"

40 / 40 papers shown

Title
Guessing Efficiently for Constrained Subspace Approximation Aditya Bhaskara S. Mahabadi Madhusudhan Reddy Pittu A. Vakilian David P. Woodruff 40 0 0 29 Apr 2025
Distributed Clustering based on Distributional Kernel Hang Zhang Yang Xu Lei Gong Ye Zhu Kai Ming Ting 18 0 0 14 Sep 2024
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning Michal Dereziñski Christopher Musco Jiaming Yang 42 2 0 09 May 2024
No Dimensional Sampling Coresets for Classification M. Alishahi Jeff M. Phillips 39 1 0 07 Feb 2024
Learning the Positions in CountSketch Yi Li Honghao Lin Simin Liu A. Vakilian David P. Woodruff 29 18 0 11 Jun 2023
Exact Non-Oblivious Performance of Rademacher Random Embeddings Maciej Skorski Alessandro Temperoni 11 0 0 21 Mar 2023
Replicable Clustering Hossein Esfandiari Amin Karbasi Vahab Mirrokni Grigoris Velegkas Felix Y. Zhou 29 13 0 20 Feb 2023
Learning Sparsity and Randomness for Data-driven Low Rank Approximation Tiejin Chen Yicheng Tao 11 0 0 15 Dec 2022
Dynamic Tensor Product Regression Aravind Reddy Zhao-quan Song Licheng Zhang 45 20 0 08 Oct 2022
Sample Efficient Learning of Factored Embeddings of Tensor Fields Taemin Heo Chandrajit L. Bajaj MedIm 11 0 0 01 Sep 2022
Explainable k-means. Don't be greedy, plant bigger trees! K. Makarychev Liren Shan 24 22 0 04 Nov 2021
Newton-LESS: Sparsification without Trade-offs for the Sketched Newton Update Michal Derezinski Jonathan Lacotte Mert Pilanci Michael W. Mahoney 37 26 0 15 Jul 2021
Near-optimal Algorithms for Explainable k-Medians and k-Means K. Makarychev Liren Shan 25 25 0 02 Jul 2021
Adversarial Robustness of Streaming Algorithms through Importance Sampling Vladimir Braverman Avinatan Hassidim Yossi Matias Mariano Schain Sandeep Silwal Samson Zhou AAML OOD 24 38 0 28 Jun 2021
Lifelong Learning with Sketched Structural Regularization Haoran Li A. Krishnan Jingfeng Wu Soheil Kolouri Praveen K. Pilly Vladimir Braverman CLL 22 17 0 17 Apr 2021
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra Nadiia Chepurko K. Clarkson L. Horesh Honghao Lin David P. Woodruff 19 24 0 09 Nov 2020
Hutch++: Optimal Stochastic Trace Estimation R. A. Meyer Cameron Musco Christopher Musco David P. Woodruff 18 103 0 19 Oct 2020
A Framework for Private Matrix Analysis Jalaj Upadhyay Sarvagya Upadhyay 24 4 0 06 Sep 2020
Scalable Initialization Methods for Large-Scale Clustering J. Hämäläinen T. Kärkkäinen T. Rossi 15 2 0 23 Jul 2020
Fair clustering via equitable group representations Mohsen Abbasi Aditya Bhaskara Suresh Venkatasubramanian FaML FedML 31 86 0 19 Jun 2020
Precise expressions for random projections: Low-rank approximation and randomized Newton Michal Derezinski Feynman T. Liang Zhenyu A. Liao Michael W. Mahoney 32 23 0 18 Jun 2020
Coresets for Clustering in Euclidean Spaces: Importance Sampling is Nearly Optimal Lingxiao Huang Nisheeth K. Vishnoi 13 76 0 14 Apr 2020
On Coresets for Support Vector Machines M. Tukan Cenk Baykal Dan Feldman Daniela Rus 27 27 0 15 Feb 2020
Learning-Based Low-Rank Approximations Piotr Indyk A. Vakilian Yang Yuan 37 67 0 30 Oct 2019
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation H. Diao Rajesh Jayaram Zhao-quan Song Wen Sun David P. Woodruff 16 43 0 29 Sep 2019
De-anonymization Attacks on Neuroimaging Datasets V. Ravindra A. Grama 15 16 0 08 Aug 2019
Tight Sensitivity Bounds For Smaller Coresets Alaa Maalouf Adiel Statman Dan Feldman 24 18 0 02 Jul 2019
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$ -means Clustering Manuel Fernández David P. Woodruff T. Yasuda 26 6 0 15 May 2019
Scalable Fair Clustering A. Backurs Piotr Indyk Krzysztof Onak B. Schieber A. Vakilian Tal Wagner 17 197 0 10 Feb 2019
Contrastive Multivariate Singular Spectrum Analysis Abdi-Hakin Dirie Abubakar Abid James Zou 6 11 0 31 Oct 2018
A Practical Algorithm for Distributed Clustering and Outlier Detection Jiecao Chen Erfan Sadeqi Azer Qin Zhang 18 25 0 24 May 2018
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? Cameron Musco David P. Woodruff 20 13 0 05 Nov 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data J. Tropp A. Yurtsever Madeleine Udell V. Cevher 23 79 0 18 Jun 2017
Scalable Kernel K-Means Clustering with Nystrom Approximation: Relative-Error Bounds Shusen Wang Alex Gittens Michael W. Mahoney 30 127 0 09 Jun 2017
Relative Error Tensor Low Rank Approximation Zhao-quan Song David P. Woodruff Peilin Zhong 22 122 0 26 Apr 2017
On the Local Structure of Stable Clustering Instances Vincent Cohen-Addad Chris Schwiegelshohn 33 47 0 29 Jan 2017
Practical sketching algorithms for low-rank matrix approximation J. Tropp A. Yurtsever Madeleine Udell V. Cevher 22 201 0 31 Aug 2016
LazySVD: Even Faster SVD Decomposition Yet Without Agonizing Pain Zeyuan Allen-Zhu Yuanzhi Li 23 128 0 12 Jul 2016
Compressive Spectral Clustering Nicolas M Tremblay Gilles Puy Remi Gribonval P. Vandergheynst 18 112 0 05 Feb 2016
Improved Distributed Principal Component Analysis Maria-Florina Balcan Vandana Kanchanapally Yingyu Liang David P. Woodruff 42 148 0 25 Aug 2014